Ai Assisted Decision Making: Research Area — Prolific Citations Library

Discover 4 peer-reviewed studies in Ai Assisted Decision Making (2024–2025). Explore research findings powered by Prolific's diverse participant panel.

This page lists 4 peer-reviewed papers in the research area of Ai Assisted Decision Making in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.

Papers (4 of 4)

To rely or not to rely? evaluating interventions for appropriate reliance on large language models

Authors: JY Bo, S Wan, A Anderson

Year: 2025

Published in: Proceedings of the 2025 CHI Conference ..., 2025 - dl.acm.org

Institution: University of Toronto

Research Area: Appropriate reliance on LLM, Human-Computer Interaction (HCI), AI-assisted decision making.

Discipline: Human-Computer Interaction (HCI)

This paper explores the latest advancements and key trends in the field of Human-Computer Interaction (HCI), focusing on novel interfaces and user experience paradigms.

Citations: 25
Imperfections of XAI: phenomena influencing AI-assisted decision-making

Authors: P Spitzer, K Morrison, V Turri, M Feng, A Perer

Year: 2025

Published in: ACM Transactions on ..., 2025 - dl.acm.org

Institution: Carnegie Mellon University, Karlsruhe Institute of Technology, University of Bayreuth

Research Area: Explainable AI (XAI), AI-Assisted Decision-Making, Human-AI Collaboration

Discipline: Artificial Intelligence

The study highlights how imperfect explainable AI (XAI), along with human cognitive styles, affects reliance on AI and the performance of human–AI teams, providing design guidelines for better collaboration systems.

Methods: The researchers conducted a study with 136 participants, analyzing the effects of explanation imperfections and cognitive styles on AI-assisted decision-making and human–AI collaboration.

Key Findings: The impact of incorrect explanations and explanation modalities on human reliance, decision-making, and human–AI team performance, as well as the role of cognitive styles.

Citations: 2

Sample Size: 136
Understanding the Role of Explanation Modality in AI-assisted Decision-making

Authors: V Robbemond, O Inel, U Gadiraju

Year: 2024

Published in: ... of the 30th ACM Conference on ..., 2022 - dl.acm.org

Institution: V Robbemond: Delft University of Technology, O Inel: Delft University of Technology, U Gadiraju: Delft University of Technology

Research Area: Explanation Modality in AI-assisted Decision Making

Discipline: Human-Computer Interaction (HCI)

The study explores the role of explanation modalities in AI-assisted credibility assessment tasks, finding that combined modalities (text and/or audio with graphics) enhance accuracy, trust, and usability compared to single-modality approaches.

Methods: A between-subjects experiment was conducted with six explanation modalities to evaluate their influence on user performance, trust, and usability in credibility assessments.

Key Findings: The effects of different explanation modalities on decision accuracy, system trust, and usability in an AI-assisted credibility assessment system.

DOI: 10.1145/3503252.3531311

Citations: 47

Sample Size: 375
Confirmation bias in AI-assisted decision-making: AI triage recommendations congruent with expert judgments increase psychologist trust and recommendation acceptance

Authors: A Bashkirova, D Krpan

Year: 2024

Published in: Science Direct

Institution: London School of Economics and Political Science

Research Area: AI-assisted Decision Making, Confirmation Bias, Professional Trust, Psychology, AI Bias

Discipline: Behavioral Science, Psychology